Pregnancy

Neural Decoding of Ultrasound-Modulated Pain States via Deep Learning: Insights from Functional Magnetic Resonance Imaging Data.

Focused ultrasound (FUS) is a noninvasive neuromodulation technique capable of modulating deep-brain circuits with millimeter precision. When combined with functional magnetic resonance imaging (fMRI), it enables causal decoding of brain-state dynamics in vivo. In this study, the authors applied deep learning to fMRI data acquired from nonhuman primates during thermal pain stimulation with and wit...

Multifeature Ultrasound-Based Classification for Breast Lesions: A Comparative Study of PONS Image Enhancement Technology.

OBJECTIVE: To overcome critical limitations of B-mode ultrasound in artificial intelligence diagnostics-including poor image quality and operator variability-by developing a multifeature framework that combines raw B-mode scans with 2 optimized representations (enhanced ultrasound and quality-improved ultrasound) for robust breast cancer classification. PATIENTS AND METHODS: We conducted a retrosp...

Fetal Sleep: A Cross-Species Review of Physiology, Measurement, and Classification.

STUDY OBJECTIVES: Fetal sleep is a vital yet underexplored aspect of prenatal neurodevelopment. Its cyclic organization reflects the maturation of cen...

Low-complexity fetal heart rate monitoring from carbon-based single-channel dry electrodes maternal electrocardiogram.

Objective. Fetal and maternal health during pregnancy can be monitored with sensors such as Doppler or scalp fetal ECG. This study focuses on single-c...

AI-Based D-Amino Acid Substitution for Optimizing Antimicrobial Peptides to Treat Multidrug-Resistant Bacterial Infection.

D-amino acid substitution provides an effective strategy for optimizing antimicrobial peptides (AMPs) by enhancing their stability. However, the absen...

Artificial Intelligence and the Potential Transformation of Mental Health.

IMPORTANCE: The potential of tools using artificial intelligence (AI) to address the many challenges in delivery of mental health care has been widely...

Assessment of AI-generated responses to common pregnancy questions: A blinded expert evaluation.

INTRODUCTION: We conducted a cross-sectional, blinded expert evaluation of AI-generated answers to 22 frequently asked pregnancy questions to characte...

Pixel-level Radiomics and Deep Learning for Predicting Ki-67 Expression in Breast Cancer Based on Dual-modal Ultrasound Images.

RATIONALE AND OBJECTIVES: This study aimed to develop a deep learning model using a novel pixel-level radiomics approach based on two-dimensional (2D)...

Harnessing artificial intelligence for the assessment of liver fibrosis and steatosis via multiparametric ultrasound.

Artificial intelligence (AI) is revolutionizing medical imaging, particularly in chronic liver diseases assessment. AI technologies, including machine...

AI-assisted translation in oral and maxillofacial surgery: A comparative evaluation.

OBJECTIVES: English dominates scientific communication, yet non-native speakers face significant barriers in publishing. Artificial intelligence (AI) ...

SERS-based deep learning approach for early detection of gestational diabetes mellitus.

Early and precise diagnosis of gestational diabetes mellitus (GDM) is crucial for improving maternal and neonatal outcomes and reducing the risk of ad...

From Recognition to Action: Integrating Deep Learning and Robotic Control in Transthoracic Echocardiography.

Population aging has driven a rise in heart failure cases, increasing the clinical burden on cardiac diagnostics. As a first-line imaging method, tran...

Neural networks for faster laser ultrasound tomography in tissue phantoms.

Speed of sound (SoS) mapping provides quantitative and localised information about a material's acoustic properties, allowing identification of spatia...

Based on the umami-transformer machine learning model: Screening of umami peptides from ultrasound-assisted enzymatic hydrolysis of shiitake mushrooms and study on their flavor mechanism.

This study aimed to optimize ultrasound-assisted enzymatic hydrolysis for umami peptide preparation from shiitake mushrooms, develop a reliable predic...

Nano-AI synergy in food chemistry: smart analytical tools for quality, safety, and nutritional profiling.

The convergence of nanotechnology and artificial intelligence (AI) is revolutionizing the landscape of food chemistry, quality control, and nutritiona...

Automated detection of gallbladder stones using a deep learning algorithm on computed tomography scans.

PURPOSE: To develop and evaluate the diagnostic accuracy of a deep learning algorithm for automated gallstone detection on CT. METHODS: This retrospec...

Multimodal ultrasound assessment of ovarian reserve.

Ovarian reserve represents the quantity and quality of a woman's remaining oocytes and serves as a key indicator of reproductive potential. Accurate a...

Predicting postpartum glucose intolerance in women with gestational diabetes mellitus in primary care: A machine learning approach using XGBoost and SHAP values.

OBJECTIVE(S): To develop and internally validate an interpretable machine learning model using eXtreme Gradient Boosting (XGBoost) and Shapley Additiv...

Evaluating a negotiation training program for family caregivers of older people using a Multiphase Optimization Strategy (MOST) design and protocol.

UNLABELLED: Traditional clinical trial designs such as the isolated two-arm randomized controlled trial (RCT) do not offer robust solutions for evalua...

Utilizing artificial intelligence for the diagnosis of ocular surface squamous neoplasia with ultrasound biomicroscopy images.

PURPOSE: This study aims to develop an artificial intelligence (AI) model to assist ophthalmologists in distinguishing ocular surface squamous neoplas...